Showing papers by "Francis X. Diebold published in 2020"
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TL;DR: In this article, the Aruoba-Diebold-Scotti Index of Business conditions (ADS) is used to track economic activity at high frequency. But the trajectory of the nascent recovery is highly uncertain, particularly as COVID-19 spreads in the South and West.
Abstract: We study the real-time signals provided by the Aruoba-Diebold-Scotti Index of Business conditions (ADS) for tracking economic activity at high frequency. We start with exit from the Great Recession, comparing the evolution of real-time vintage beliefs to a "final" late-vintage chronology. We then consider entry into the Pandemic Recession, again tracking the evolution of real-time vintage beliefs. ADS swings widely as its underlying economic indicators swing widely, but the emerging ADS path as of this writing (late June) indicates a return to growth in May. The trajectory of the nascent recovery, however, is highly uncertain -- particularly as COVID-19 spreads in the South and West -- and could be revised or eliminated as new data arrive.
13 citations
TL;DR: Based on several decades of satellite data, the authors provided statistical forecasts of Arctic sea ice extent during the rest of this century, which indicated that overall sea ice coverage is declining at an increasing rate.
13 citations
TL;DR: In this paper, the Aruoba-Diebold-Scotti Index of Business conditions (ADS) is used to track economic activity at high frequency. But the trajectory of the nascent recovery is highly uncertain, particularly as COVID-19 spreads in the South and West.
Abstract: We study the real-time signals provided by the Aruoba-Diebold-Scotti Index of Business conditions (ADS) for tracking economic activity at high frequency. We start with exit from the Great Recession, comparing the evolution of real-time vintage beliefs to a “final” late-vintage chronology. We then consider entry into the Pandemic Recession, again tracking the evolution of real-time vintage beliefs. ADS swings widely as its underlying economic indicators swing widely, but the emerging ADS path as of this writing (late June) indicates a return to growth in May. The trajectory of the nascent recovery, however, is highly uncertain – particularly as COVID-19 spreads in the South and West – and could be revised or eliminated as new data arrive.
10 citations
Posted Content•
TL;DR: The authors studied the real-time signals provided by the Aruoba-Diebold-Scotti Index of Business conditions (ADS) for tracking economic activity at high frequency and found that the emerging ADS path as of this writing indicates a return to growth in May.
Abstract: We study the real-time signals provided by the Aruoba-Diebold-Scotti Index of Business conditions (ADS) for tracking economic activity at high frequency We start with exit from the Great Recession, comparing the evolution of real-time vintage beliefs to a "final" late-vintage chronology We then consider entry into the Pandemic Recession, again tracking the evolution of real-time vintage beliefs ADS swings widely as its underlying economic indicators swing widely, but the emerging ADS path as of this writing (late June) indicates a return to growth in May The trajectory of the nascent recovery, however, is highly uncertain (particularly as COVID-19 spreads in the South and West) and could be revised or eliminated as new data arrive
5 citations
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TL;DR: In this article, a dynamic factor model was proposed to combine four different measures of Arctic sea ice extent in an optimal way that accounts for their differing volatility and cross-correlations.
Abstract: The diminishing extent of Arctic sea ice is a key indicator of climate change as well as an accelerant for future global warming. Since 1978, Arctic sea ice has been measured using satellite-based microwave sensing; however, different measures of Arctic sea ice extent have been made available based on differing algorithmic transformations of the raw satellite data. We propose and estimate a dynamic factor model that combines four of these measures in an optimal way that accounts for their differing volatility and cross-correlations. We then use the Kalman smoother to extract an optimal combined measure of Arctic sea ice extent. It turns out that almost all weight is put on the NSIDC Sea Ice Index, confirming and enhancing confidence in the Sea Ice Index and the NASA Team algorithm on which it is based.
4 citations
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TL;DR: In this paper, the authors study the evolution of real-time vintage beliefs and compare them to a later-vintage chronology, and provide a comparative assessment of the realtime ADS signals provided when exiting the Great Recession, concluding that daily real activity path was highly correlated with the daily COVID-19 cases.
Abstract: Entering and exiting the Pandemic Recession, I study the high-frequency real-activity signals provided by a leading nowcast, the ADS Index of Business Conditions produced and released in real time by the Federal Reserve Bank of Philadelphia. I track the evolution of real-time vintage beliefs and compare them to a later-vintage chronology. Real-time ADS plunges and then swings as its underlying economic indicators swing, but the ADS paths quickly converge to indicate a return to brisk positive growth by mid-May. We show, moreover, that daily real activity path was highly correlated with the daily COVID-19 cases. Finally, I provide a comparative assessment of the real-time ADS signals provided when exiting the Great Recession.
2 citations
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TL;DR: The origin(s) of the term "Big Data," in industry and academics, and in computer science and econometrics is investigated, finding that it probably originated in lunch-table conversations at Silicon Graphics Inc. in the mid 1990s.
Abstract: I investigate the origin(s) of the term "Big Data," in industry and academics, and in computer science and econometrics. The term probably originated in lunch-table conversations at Silicon Graphics Inc. (SGI) in the mid 1990s, in which John Mashey figured prominently. The first significant (and independent) academic references are arguably Weiss and Indurkhya (1998) in computer science and Diebold (2000) in econometrics. An unpublished 2001 research note by Douglas Laney at Gartner enriched the concept significantly. The Big Data phenomenon continues unabated.
1 citations
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TL;DR: This article explored a variety of objectives and regularization penalties and used them in a substantive exploration of Eurozone inflation and real interest rate density forecasts, finding that the optimal regularization tends to move density forecasts' probability mass from the centers to the tails, correcting for overconfidence.
Abstract: We propose methods for constructing regularized mixtures of density forecasts. We explore a variety of objectives and regularization penalties, and we use them in a substantive exploration of Eurozone inflation and real interest rate density forecasts. All individual inflation forecasters (even the ex post best forecaster) are outperformed by our regularized mixtures. From the Great Recession onward, the optimal regularization tends to move density forecasts' probability mass from the centers to the tails, correcting for overconfidence.
1 citations
Posted Content•
TL;DR: In this article, the origins of the term "big data" are investigated, involving both academics and industry, statistics and computer science, ultimately winding back to lunch-table conversations at Silicon Graphics Inc. (SGI) in the mid 1990s.
Abstract: Against the background of explosive growth in data volume, velocity, and variety, I investigate the origins of the term "Big Data". Its origins are a bit murky and hence intriguing, involving both academics and industry, statistics and computer science, ultimately winding back to lunch-table conversations at Silicon Graphics Inc. (SGI) in the mid 1990s. The Big Data phenomenon continues unabated, and the ongoing development of statistical machine learning tools continues to help us confront it.
TL;DR: Christoffersen as discussed by the authors was a world-renowned financial econometrics resarcher, educator, lecturer, administrator, and public servant (including the U.S. Federal Reserve System’s Model Validation Committee, charged with reviewing the models used for bank supervision and regulation).
Abstract: Peter F. Christoffersen left us in 2018, much too soon, at the age of 51. He was a world-renowned financial econometrics resarcher, educator, lecturer, administrator (including hosting the 2014 SoFiE conference at the University of Toronto), and public servant (including the U.S. Federal Reserve System’s Model Validation Committee, charged with reviewing the models used for bank supervision and regulation). If Peter was an esteemed colleague, he was equally a dear friend. His unbridled optimism, relaxed personality, and remarkable humility endeared him to all who knew him. We honor Peter’s path-breaking research in this special issue. Its style is marked by a masterful blend of intuition, theoretical rigor, and always, empirical relevance. It influenced and inspired countless others in academics and industry, world-wide. It has four basic, and highly-intertwined, organizational themes: